Biomedical subjects

Jayprokas Chakrabarti

Publications and source records attributed to Jayprokas Chakrabarti.

4 recordsLinked to original sources

PubMed2005

tRNA-isoleucine-tryptophan composite gene.

Transfer-RNA genes in archaea often have introns intervening between exon sequences. The structural motif at the boundary between exon and intron is the bulge-helix-bulge. Computational investigations of these boundary structures in Haloarcula marismortui lead us to propose that tRNA-isoleucine and tRNA-tryptophan genes are co-located. Precise in silico identification of the splice-sites on the bulges at the exon-intron boundaries lead us to infer that a single intron-containing composite tRNA-gene can give rise to more than one gene product.

Animals↗

PubMed2005

A new measure to study phylogenetic relations in the brown algal order Ectocarpales: the "codon impact parameter".

We analyse forty-seven chloroplast genes of the large subunit of RuBisCO, from the algal order Ectocarpales, sourced from GenBank. Codon-usage weighted by the nucleotide base-bias defines our score called the codon-impact-parameter. This score is used to obtain phylogenetic relations amongst the 47 Ectocarpales. We compare our classification with the ones done earlier.

Base Composition↗

PubMed2005

Identity elements of archaeal tRNA.

Features unique to a transfer-RNA are recognized by the corresponding tRNA-synthetase. Keeping this in view we isolate the discriminating features of all archaeal tRNA. These are our identity elements. Further, we investigate tRNA-characteristics that delineate the different orders of Archaea.

Amino Acyl-tRNA Synthetases↗

PubMed2003

Temporal changes in phosphoglycerate kinase coding sequences: a quantitative measure.

The ratio of the average of the square of the number of the nucleotides to that of the random sequence of the same strand bias is proposed as a quantitative measure of evolution in some coding DNA sequences. Applying this measure to the phosphoglycerate kinase gene we observe a monotonic rise of the ratio with evolution. We present an interpretation of this data on some bacteria.

Algorithms↗